Interkingdom assemblages in human saliva display group-level surface mobility and disease-promoting emergent functions

Significance Fungi and bacteria form multicellular biofilms causing many human infections. How such distinctive microbes act in concert spatiotemporally to coordinate disease-promoting functionality remains understudied. Using multiscale real-time microscopy and computational analysis, we investigate the dynamics of fungal and bacterial interactions in human saliva and their biofilm development on tooth surfaces. We discovered structured interkingdom assemblages displaying emergent functionalities to enhance collective surface colonization, survival, and growth. Further analyses revealed an unexpected group-level surface mobility with coordinated “leaping-like” and “walking-like” motions while continuously growing. These mobile groups of growing cells promote rapid spatial spreading of both species across surfaces, causing more extensive tooth decay. Our findings show multicellular interkingdom assemblages acting like supraorganisms with functionalities that cannot be achieved without coassembly.

In-situ mechanical resistance and antimicrobial tolerance of surface-attached biostructures. The mechanical stability of surface-attached microbial biostructures was investigated by applications of fluid shear stress and assessment of surface detachment via a flow-cell microfluidic imaging device (BioSurface Technologies). The sHA disk with the pre-stained (Syto9 for S. mutans and Concanavalin Atetramethylrhodamine for C. albicans), surface-attached biostructures was gently washed to remove loosely bound microbes and mounted in the flow-cell microfluidic device. The device was connected downstream to a digital peristaltic pump (Cole-Parmer) and was coupled with the Zeiss LSM800 confocal microscopy. Disks were subjected to a controllable flow (from 0.1 to 200 mL/min). The Computational Fluid Dynamics module of COMSOL Multiphysics (V5.2) was used to estimate the fluidic wall shear stress at the surface on which the biostructures were attached. This setup allows applying varying wall shear stress ranging from 0.001 to 20 Pa and assessing the detachment of the assemblages in real-time using confocal imaging. Each fluid sheer stress was applied for 60 s then paused during image acquisition. The multi-channel confocal image was subject to thresholding and the biovolume was determined. For interkingdom assemblages, the remaining biovolume was calculated as the total biovolume of S. mutans and C. albicans that remained on the surface after the flow. Relative mechanical resistance is defined as the ratio of remaining biovolume on the surface to the original biovolume. To investigate the tolerance of the biostructures to antimicrobials, we developed an in-situ cell viability staining and imaging technique allowing real-time visualization of killed microbial cells, based on modifications of our previous protocol (10). Briefly, disks with surface-attached microbes were pre-stained with Syto9 for S. mutans and with Concanavalin Atetramethylrhodamine for C. albicans. The disks were immersed in 1 µM Toto-3 (Molecular Probes), a cell impermeable dimeric cyanine acid dye as a real-time cell death indicator for both bacteria and fungi (10). The time point denoted as "0 min" corresponds to the first confocal image acquisition before adding the antimicrobial agent. Chlorhexidine (100 µg/mL), a commonly used broad-spectrum antimicrobial used in dental clinics that can kill both bacteria and fungi (11) and nystatin (250 µg/mL), a clinically used oral fungicide that has no killing effect on bacteria (12) were used as model antimicrobial agents. We also quantitatively assessed the antimicrobial resistance of fungal/bacterial cells in different biostructures by determining the residual viable cell number (CFU) of C. albicans and S. mutans after the treatment (5 min after chlorhexidine or 20 min after nystatin treatment). To test whether EPS α-glucan degradation could affect the mechanical and antimicrobial resistance, the disks with the attached biostructures were pretreated with glucanohydrolases (dextranase and mutanase) that specifically break down the α-glucans produced by S. mutans (9) before the experiment.
Dynamics of biofilm initiation from interkingdom assemblage. Biofilm growth dynamics and spatial organization of individual aggregates were tracked by a time-lapsed confocal imaging system coupled with flow-cell microfluidics, based on our continuous flow-cell labelling and confocal imaging protocol (13). The HA disk with the initial colonizing community (including interkingdom assemblages and single cells) were pre-stained with 0.1 μM Syto9 to label S. mutans cells. We used the fluorescent C. albicans SN250 strain (C. albicans SN250 tdTomato) for tracking the fungal cells. Then, the disk was gently washed to remove loosely bound microbes and aseptically transferred into a flow-cell microfluidics device (FC310, BioSurface Technologies) for biofilm development analysis via time-lapsed confocal imaging. UFTYE medium supplemented with 25% saliva and 1% sucrose was continuously provided (100 μL/min) using a peristaltic pump to mimic the natural nutrient condition of dental plaque in the oral cavity. The medium was supplemented with 250 nM Syto9 to allow continuous bacterial cell labelling in the growing biofilm. The concentration was pre-determined to yield optimized bacterial cell labeling without negative effects on cell growth (6). Bacterial EPS glucan matrices were labeled via supplementing the culture medium with 1 μM Alexa Fluor 647 dextran conjugate (Molecular Probes) during biofilm growth. This labeling method is highly specific for S. mutans-derived α-glucans since the fluorescently-labeled dextrans serve as primers for streptococcal Gtfs and are directly incorporated into glucans during biofilm EPS synthesis (2). Time-lapsed confocal imaging (z-stacks of 0.31-μm pixel size and 1 μm z-step) was performed every 30 min at 37 °C using a 40× water-immersion objective (numerical aperture = 1.2) on the Zeiss LSM800 microscope with Airyscan functionality. The growing biofilm was sequentially scanned (488/640-nm lasers for Syto9/Alexa Fluor 647-dextran, then 561-nm laser for Concanavalin A-tetramethylrhodamine) and the emitted signal was collected using optimum emission wavelength filters. Image visualization was performed using ImageJ Fiji (https://imagej.net/Fiji).
General image processing. Computational image processing and quantitative analysis were performed following established protocols using BiofilmQ software (https://drescherlab.org/data/biofilmQ) (14), an image analysis toolbox optimized for biofilms. Briefly, multi-channel raw images (S. mutans, C. albicans, and EPS) were imported into BiofilmQ and the stage drift (for time-lapse imaging data) was corrected using the image alignment function. Individual microbial biostructures (interkingdom assemblage, aggregated S. mutans, and aggregates C. albicans) were cropped to generate designated datasets. After average filtering, each channel of the image was segmented using Otsu algorithm with 2 classes, multiplied with a sensitivity value of 0.35. The thresholding result was verified visually by users and further optimized when needed to ensure precise segmentation. After segmentation, a cube-based object declumping was performed, which dissected a larger biofilm volume into small cubic volumes. A cube side length of 10 pixels was used for biovolume or surface coverage measurements and a 4-pixel cube was used for spatial measurements. This function allows further analysis of biofilm properties inside the biofilm volume with spatial resolution because each cube has a unique spatial coordinate in 3D.

Computational structural analysis and tracking.
Computational structural analysis and tracking were performed using BiofilmQ in combination with customized MATLAB scripts to generate specific plots (14). In brief, for spatial measurements, the three segmented (binarized) channels corresponding to S. mutans, C. albicans, and EPS were merged using BiofilmQ. The object parameter "RelativeAbundance_chx" was used to measure the biovolume abundance for each channel within each cube. To determine the distribution of each components (C. albicans, S. mutans, or EPS) over the height of the microbial structure (i.e., from the surface to the top of the structure), the cubes were assigned into horizontal sections (thickness = 2.5 µm) parallel to the surface at different heights, based on the z-coordinate of each cube. The mean relative abundance in each section was calculated and the height was normalized by the z-coordinate (vertical position) of the microbial structure's center-of-mass (or "centroid"). The resulting spatial distribution curves were smoothed using MATLAB's built-in smooth function. To measure the biofilm volume over time, the global parameter "Biofilm_Volume" in BiofilmQ was used. To ensure a meaningful comparison, each growth curve was normalized by the initial biovolume, defined as the mean of the BiofilmQ parameter "Biofilm_Volume" of the timepoints t1.5h, t2h, and t2.5h. These timepoints were determined to have improved signal-to-noise ratio than those earlier than 1.5 h, leading to optimized normalization with minimal systemic error. For the group-level bacterial mobility tracking, we determined the biovolume centroid of the bacterial clusters over time based on the segmentation performed in BiofilmQ. Time-resolved 3D trajectories were generated using the spatial coordinates of the bacterial biomass at each timepoint. The accumulated S. mutans displacement (total path length) of the bacterial centroid relative to the initial position was calculated. We also analyzed the dynamics of biofilm surface coverage, which was defined as the sum of all segmented pixels of the largest connected object in the z-projection on the entire surface, normalized by the mean value across t1.5h, t2h, and t2.5h (due to improved signal-to-noise ratio than the earlier timepoints). The Code Availability section describes how the customized MATLAB codes used for the computational image analysis can be obtained.
Ex-vivo human tooth-enamel biofilm model. To investigate the disease-promoting functions of the interkingdom assemblage, we employed an ex-vivo human tooth-enamel model which allows simultaneous analysis of the biofilm spatial structure and the extent of enamel decay underneath (15). Briefly, interkingdom assemblage, aggregated S. mutans, or aggregates C. albicans were allowed to bind onto vertically-mounted sterilized human enamel specimens (4 mm × 4 mm) following the same protocol as detailed in Experimental model for interkingdom assemblage and surface colonization in saliva. The enamel specimens were gently washed in 0.9% sodium chloride solution to remove loosely bound microorganisms and were incubated in filter-sterilized human saliva supplemented with 1% sucrose at 37 °C and 5% CO2 for 67 h (medium changed twice daily). No additional bacterial or fungal cells were inoculated into the salivabased medium, except those within the initially attached biostructures. The biofilm structural organization on the tooth-enamel surface was assessed via a multilabelling approach. Bacterial EPS glucans were labeled via supplementing the saliva medium with 1 μM Alexa Fluor 647 dextran conjugate. At the end of the experiment, biofilms formed on the tooth-enamel surface were stained using Syto9 (for S. mutans) and Concanavalin A-tetramethylrhodamine (for C. albicans). The 3D biofilm structure formed on the toothenamel surface was imaged using a 20× water-immersion objective (numerical aperture = 1.0) on the Zeiss LSM800 system. Amira software (version 5.4.1) was used to generate 3D renderings of the biofilm architecture.

Enamel surface analyses.
To assess the enamel structural damage and mineral loss, we conducted multiscale surface analyses after removing the biofilms from the tooth enamel (15,16). In brief, after biofilm imaging, the biomass was removed using enzymatic treatment (dextranase and mutanase) followed by water bath sonication, which was optimized for biofilm removal without causing artificial surface damage (15). Macroscopically, the demineralized areas on tooth-enamel surfaces (similar to those found clinically in severe childhood tooth-decay) were visualized using a stereomicroscope (Zeiss AxioZoom V16). Then, the surface topography and roughness of the tooth-enamel surface were assessed by a non-destructive confocal topography analysis using a 50× (numerical aperture = 0.95) objective on the Zeiss LSM800 microscope following previously reported protocols (15). The 3D microtopography datasets were processed using ConfoMap software (Zeiss) to generate surface properties and 3D surface renderings. Next, the toothenamel specimens were mounted on acrylic rods and sectioned (100 ± 20 thickness) with a hard tissue microtome (Silverstone-Taylor Hard Tissue Microtome, Series 1000 Deluxe) for transversal microradiography. The sections were placed in the TMR-D system and x-rayed at 45 kV and 45 mA at a fixed distance, for 12 s. An aluminum step wedge was X-rayed under identical conditions. The digital images were analyzed using the TMR software v.3.0.0.18, with sound enamel defined at 87% mineral volume (17). Figure S1. Fluorescence in situ hybridization of native-state interkingdom assemblages in saliva from patients with early childhood caries. Saliva from children with severe childhood caries was collected and the naturally-present microbial structure was analyzed by super-resolution confocal imaging and fluorescence in situ hybridization (FISH) using species-specific probes (two examples are shown). Saliva from patients was enriched with assemblages comprised primarily of S. mutans clusters (green) which were physically associated with C. albicans cells (cyan) in yeast and hyphal/pseudo-hyphal forms, building a multicellular structure in the saliva fluid. Scale bar, 10 μm.

Figure S2. EPS α-glucans formed on the bacterial and fungal cell surfaces of the interkingdom assemblage and glucosyltransferases (Gtf) activity in saliva.
(A) α-Glucans were found on the microbial surfaces of the assemblages in the saliva from patients with early childhood caries using an ex vivo glucan detection assay. Cyan, fungal hypha; green, bacteria; red, EPS α-Glucans. Scale bar, 2 μm. (B) Total Gtf enzyme activity in the saliva from healthy (caries-free) and diseased children determined by radiolabeling and scintillation counting. The total Gtf activity in saliva (containing S. mutans-derived Gtfs and Gtfs from other species) was measured. Data are presented as median with interquartile range (N ≥ 4). *, p < 0.05 by Mann-Whitney test.    assemblages formed by C. albicans wild type strain with S. mutans double-mutant of gtfB and gtfC, and the assemblage formed by wild type C. albicans and S. mutans in the presence of EPS-degrading enzymes (dextranase and mutanase), and (B2) CFU counts of both species recovered from the surface. For all the tested combinations, a defined population (10 5 CFU/mL for C. albicans and 10 7 CFU/mL for S. mutans) was used as the inoculum. Groups that do not share an uppercase letter (for S. mutans) or a lowercase letter (for C. albicans) are significantly different (p < 0.05) by one-way analysis of variance with Tukey's multiplecomparison test). Abbreviation: C.a., C. albicans; S.m., S. mutans. Scale bars, 10 μm. Figure S7. Surface colonization of interkingdom assemblages formed by C. albicans and S. mutans in the absence of sucrose. Confocal image of surface-attached assemblages formed by wild type C. albicans (in cyan) and S. mutans (in green) in the presence or absence of 1% sucrose. In the absence of sucrose, the substrate for streptococcal Gtf enzymes to synthesize EPS α-glucans, the ability of C. albicans and S. mutans to colonize as structured interkingdom assemblages was impaired. Abbreviation: C.a., C. albicans; S.m., S. mutans. Scale bars, 10 μm.   are visualized using TOTO-3 iodide (in red). Left image in the box illustrates C. albicans-S. mutans assemblage (with and without EPS degradation by dextranase and mutanase) or C. albicans-S. gordonii assemblage prior to antimicrobial exposure. Images on the right show the real-time killing profile (red channel only) within the same surface-attached assemblage. White solid lines indicate the bacterial clusters within interkingdom assemblages. The data show that the microbes in the C. albicans-S. mutans assemblage (after EPS α-glucan degradation) and in the C. albicans-S. gordonii assemblage were effectively and homogeneously killed by chlorhexidine (100 µg/mL). Color scheme: Green, bacteria (S. mutans or S. gordonii); cyan, C. albicans; red, dead cells (bacteria and C. albicans). Abbreviation: Assembl, interkingdom assemblage; C.a., C. albicans; S.m., S. mutans; S.g., S. gordonii. Scale bar, 20 μm. Figure S11. Disruption of bacterial attachment to the Candida hyphae and the "hitch-hiking" growth behavior. Orthogonal projections of time-lapse confocal images of growing interkingdom assemblages with continuous EPS α-glucan degradation. Glucanohydrolases (dextranase and mutanase) were continuously provided in the culture medium flow which causes degradation of EPS α-glucan within the surface-attached assemblage, preventing new glucan synthesis and accumulation. In these conditions, bacterial attachment to the Candida hyphae was impaired despite growth of both species, and therefore the bacterial cells could not "hitch-hike" on the developing fungi, suggesting that α-glucan degradation could disrupt this mode of mobility. Color scheme: Green, S. mutans; cyan, C. albicans. Yellow arrow, bacteria clusters detached from the fungi during the growth. Abbreviation: C.a., C. albicans; S.m., S. mutans. Scale bar, 50 μm.